Academic Projects

Detection of Uncovered Background and Moving Pixels

Abstract: In this project a binary hypothesis test for the detection of uncovered background and moving pixels between image frames in a noisy image sequence has been formulated and evaluated. White Gaussian noise has been assumed. I have extended the binary hypothesis test to 3-ary hypothesis test, such that, the three segmentation regions are uncovered background, stationary and moving pixels. I have formulated the Bayes decision rule using a single intensity-difference measurement at each pixel. I have quantitatively evaluated the detection algorithm on an image sequence which I have generated.

Abstract: A review of the physics applicable to laser induced fluorescence imaging of uranium was conducted. It was determined that solid state physic would dominate, leading to several channels of data from the scanner. A single input adaptive filter was chosen to improve the performance of the detection system. The filter was simulated under the condition of a variable background and additive noise. The simulations demonstrated an improved performance under these conditions.

Abstract: The aim of this project is to classify the mammographic masses as benign or malignant using texture and shape features. A set of 73 mammograms is used for the analysis, out of which 41 are benign and 32 are malignant. Manually segmented masses are obtained from the DDSM, USF database [2]. Texture and shape features are extracted from the manually segmented masses. Stepwise linear discriminant analysis is used to get the optimum set of features. Maximum-likelihood classifier with linear discriminant analysis (LDA) is used for the classification. The system is tested using leave-one-out test method and an overall accuracy of about 78 % is achieved.

Abstract: Fuzzy Logic is a superset of conventional (Boolean) logic that has been extended to handle the concept of partial truth, i.e. truth values between “completely true” and “completely false”. Fuzzy Logic provides a different way to approach a control or classification problem. This method focuses on what the system should do ratherthan trying to model how it works. Fuzzy approach requires a sufficient expert knowledge for the formulation of the rule base, the combination of the sets and the defuzzification. Fuzzy Logic might be helpful, for very complex processes, when there is no simple mathematical model.

Abstract: A brief overview of the role of passive microwave radiometer in climate monitoring is given in this paper. Passive microwave radiometers have been an important part of the emerging field of climate applications of satellite data. Even though the researchers in passive microwave remote sensing are less as compared to visible and infrared remote sensing, the characteristics of microwave radiometers lend themselves more readily to climate applications. I will review some of the important advances this area has seen in the last thirty years, and what the future holds. Some of the applications reviewed are TRMM, applications to land surface parameter retrieval and the effects of weather systems on sea-ice concentration.

Abstract: In automotive control, conventional cruise control systems have been available in the market for many years. A modern learning technology has a great deal to offer in the practical application of vehicle cruise control. The purpose of a cruise control system is to accurately maintain the driver’s desired set speed, without intervention from driver, by actuating the throttle-accelerator pedal linkage. Cruise control is an invaluable feature in American cars. With increasing traffic conventional cruise control is become less useful, but cruise control systems are adapting to this new reality, which leads to the concept of Adaptive Cruise Control (ACC). It maintains a safe distance between the cars. In this paper, the general information about the cruise control systems in the field of vehicle controls is discussed.

Abstract: The analysis of a remote sensing image usually requires the comparison of the analyzed image with another image taken from the same spot. In an automated object identification system for remotely sensed images, thresholding techniques are used to analyze the images. Color values and solidity features are used for object identification. In this project, the objects identified are catfish ponds. Results prove that automatic image analysis provides a good means to extract catfish ponds from remotely sensed images.